Журнал исследований и разработок

Журнал исследований и разработок
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ISSN: 2311-3278

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A Newly Improved Fatigue Life Prediction Model for Unconstrained Single Peak Plain Dents Based on EPRG Approach

Ming Gao1, Ravi Krishnamurthy1, Rick Wang2*

The objective of this ongoing work is to refine the European Pipeline Research Group’s (EPRG) methodology for fatigue life assessment of unconstrained single peak plain dents in pipelines under cyclic internal pressure. EPRG 2000 was recently adopted by the American Petroleum Institute (API) and American Society of Mechanical Engineers (ASME) (API 579/ASME FFS) as an alternative approach recommended for Level 2 plain dent fatigue life assessment. EPRG 2000, along with its earlier version, EPRG 1995, has been commonly used for dent integrity assessment in North America and worldwide because it is recommended by the highly recognized Pipeline Defect Assessment Manual (PDAM). However, Pipeline industry practice in North America found that the EPRG equations provide conservative, in many cases, very conservative predictions that resulted in unnecessary excavations and repairs. Therefore, improving the model’s accuracy and level of conservatism is essential from both safety and costeffective perspectives. In this paper, a critical review of EPRG 2000 fatigue life prediction models is performed first, which provides a basis for improvement. Development and validation of the newly improved and further refined model are then discussed. Firstly, the refinement is based on extensive dent fatigue testing conducted by the Pipeline Research Council (PRCI) (ref). Then, a comparison between the newly improved EPRG model and (PRCI) funded additional full-scale-fatigue testing and modeling adopted by API Recommended Practice 1183 (API RP 1183) Level 2 and PRCI Level 3 models is made. This ongoing work provides a methodological framework to advance studies in dent interaction with welds, gouges, cracks, and corrosion.

Отказ от ответственности: Этот тезис был переведен с использованием инструментов искусственного интеллекта и еще не прошел рецензирование или проверку.
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